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In a bit of unambiguously 21st century news, some tweaks to Grok, xAI's chatbot have had it do particularly interesting things today including
when asked to, composing bite sized smut about other users (first victim was possibly Will Stancil)., then defending said decision.
referring to itself as Mechahitler
doing the "every single time" meme in its replies.
saying Elon personally allowed it to point out Jewish overrepresentation in radical leftism
This may make minor news because Musk is in trouble, on the other hand all the people who really, really hate him have their pants on fire like Europeans, von der Leyen is getting impeached, they're actually scared of Russia / China so it might just blow over, the grid is getting worse and is going to keep getting worse due to Green energy mandates.
I'm even suspecting Musk deliberately told them to relax the guardrails for some reason. Probably .. publicity?
Update: site addresses the issues
EDIT2
EDIT3
Stancil went on local TV news to complain about the ERP grok made. (video included)
EDIT4:
There's quite reasonable suspicion this 'malfunction' was engineered by Nikita Bier
I continue to be baffled that anybody takes these bots seriously, or sees Grok or xAI or their competitors as anything other than nonsense generators. A slight change to the flavour of the nonsense doesn't really change my opinion any. Perhaps it moves me in the direction of thinking that Musk is childish and temperamental, but I already thought that, so it doesn't make much difference.
...nonsense generators? Have you ever used e.g. Gemini or Deepseek? Both are free. Okay both can be very naive at times, and both are kind of soy with default prompts. Deepseek, however, with a bit of prompting can be completely insane yet rational and easily smarter than most people you see if you go to any place outside of a professional context.
If you want to really see what they can do, install some client for LLMs and hook yourself up with some of the better free models over at https://openrouter.ai/models
(there's a 50 query daily limit if you have <10$ in your account, not sure if there's a better service. )
Even the best models will confidently spout absolute falsehoods every once in a while without any warning.
Buddy, have you seen humans?
As a math nerd I seriously despise this line of argument as it ultimately reduces to a fully generalized argument against "true", "false", and "accuracy" as meaningful concepts.
I invite further clarification.
Imagine a a trick abacus where the beads move on thier own their own via some pseudorandom process, or a pocket calculator where digits are guaranteed to a +/- 1 range. IE you plug in "243 + 67 =" and more often then not you get the answer "320" but you might just as well get the answer "310", "321" or "420". After all, the difference between all of those numbers is very small. Only one digit, and that digit is only off by one.
Now imagine you work in a field where numbers are important, you lives depend on getting this math right. Or maybe you're just doing your taxes, and the Government is going to ruin you if the accounts don't add up.
Are you going to use the trick calculator? If not, why not?
That is not an explanation for:
You're arguing that since LLMs are not perfectly reliable, therefore they're unreliable. There are different degrees of reliability necessary to do useful things with them. It is a false dichotomy to divide them so. I contend that they've crossed the threshold for many important, once well-paying lines of cognitive labor.
Besides, your thought experiment is obviously flawed. If you're sampling from a noisy distribution, what's stopping you from doing so multiple times, to reduce the error bars involved? I'd expect a "math nerd" to be aware of such techniques, or did your interest end before statistics?
If I had to rely on an LLM for truly high-stakes work, I'd be working double time to personally verify the information provided, while also using techniques like running multiple instances of the same prompt, self-critique or debate between multiple models.
Fortunately, that's a largely academic exercise, since very few issues of such consequences should be decided by even modern LLMs. I give it a generation or two before you can fire and forget.
I have no objections to my own doctor using an LLM, and I use them personally. All I ask is that they have the courtesy and common sense to use o3 instead of 4o.
Besides, the contraption you describe is quite similar to how quantum computing works. You get an answer which is sampled from a probability distribution. You are not guaranteed to get a single correct answer. Yet quantum computers are at least theoretically useful.
Hell, as a maths nerd, you should be aware that the overwhelming majority of numbers cannot be physically represented. If you also happen to be a CS nerd on the side, you might also be aware of the vagaries of floating point arithmetic. Digital computers are not perfect, but they're close enough for government work. LLMs are probably close enough for government work too, given the quality of the average bureaucrat.
Humans are fallible. LLMs are fallible, but they're becoming less so. The level of reliability needed for a commercially viable self-driving vehicle is far higher than that for a useful Roomba. And yet, Waymos are now safer than humans.
I rest my case.
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